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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The ‘Robotics: Estimation and Learning’ online course is a study about robots with the techniques and strategies involved in determining the surrounding factors during flight and movement. This online program is part of the Robotics specialization of the mechanical engineering domain that is under the physical science and engineering courses. This Robotics course is provided by the online educational platform Coursera and the curriculum is offered by the University of Pennsylvania. This self-paced learning course training is framed to be completed in fifteen hours.
The course instructor for this online training is Daniel Lee from the Electrical and Systems Engineering department. The students are ensured with the flexibility in deadlines and subtitles offered in languages such as English, Spanish, and Chinese along with the videos and other exercises that add up to an experiential learning process. The ‘Robotics: Estimation and Learning’ by Coursera enables the candidates of the program to receive a shareable certificate for recognition after completion of the course study.
The Highlights
- Online mode
- Fifteen hours course
- Robotics specialization
- Adjustable deadlines
- Subtitles
- Course certificate
Programme Offerings
- Course Modules
- videos
- Readings
- Exercises
- assignments
- quizzes
- peer feedback
- Graded Programming Assignments
- course certificate
- Self-Study Course.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Coursera |
The ‘Robotics: Estimation and Learning’ course fee can be studied for free through the audit mode or can choose the preferred payment method. The students are provided with EMI payment options.
Robotics: Estimation and Learning fee structure
Audit Mode | Free |
One Month (20+ hours/week) | ₹6,634 |
Three Months (12 hours/week) | ₹13,268 |
Six Months (6 hours/week) | ₹19,903 |
Eligibility Criteria
Certificate qualifying details
The students of the ‘Robotics: Estimation and Learning’ training course by Coursera will qualify for the course certificate by the University of Pennsylvania after completing the course study with the graded assessments.
What you will learn
The ‘Robotics: Estimation and Learning’ syllabus is structured for the students to learn about specific concepts and principles in robotics and automation that help in understanding the process of how robots identify their surroundings. The students of this program will get familiar with the detailed theories such as probabilistic generative models, Bayesian filtering for localization and mapping. This training enables candidates to gain expertise with the concepts of particle filter, estimation, and mapping in Robotics.
Who it is for
The ‘Robotics: Estimation and Learning’ online certification course is developed for the students who are interested in equipping themselves with the specific knowledge of robotics, filtering of particles done in robots, estimation techniques, and mapping of the surrounding with sensor tracking.
Admission Details
The admission for the ‘Robotics: Estimation and Learning’ online program is done by registering for the course online through the course website.
Step 1: Find the course page using the link - https://www.coursera.org/learn/robotics-learning
Step 2: Click on the ‘Enroll For Free’ link
Step 3: Follow the instructions and complete the registration.
Application Details
The candidates of the ‘Robotics: Estimation and Learning’ course will have to enter their name and email address to create the course account for registration.
The Syllabus
Videos
- Course Introduction
- WEEK 1 Introduction
- 1D Gaussian Distribution
- Maximum Likelihood Estimate (MLE)
- Multivariate Gaussian Distribution
- MLE of Multivariate Gaussian
- Gaussian Mixture Model (GMM)
- GMM Parameter Estimation via EM
- Expectation-Maximization (EM)
Readings
- MATLAB Tutorial - Getting Started with MATLAB
- Setting Up your MATLAB Environment
- Basic Probability
Assignment
- Learning Style Preference Questionnaire
Programming Assignment
- Color Learning and Target Detection
Videos
- Introduction
- Kalman Filter Motivation
- System and Measurement Models
- Maximum-A-Posterior Estimation
- Extended Kalman Filter and Unscented Kalman Filter
Programming Assignment
- Kalman Filter Tracking
Videos
- Introduction
- Introduction to Mapping
- Occupancy Grid Map
- Log-odd Update
- Handling Range Sensor
- Introduction to 3D Mapping
Programming Assignment
- 2D Occupancy Grid Mapping
Videos
- Introduction
- Odometry Modeling
- Map Registration
- Particle Filter
- Iterative Closest Point
- Closing
Programming Assignment
- Particle Filter Based Localization
Instructors
Penn Frequently Asked Questions (FAQ's)
The course is provided by Coursera and the University of Pennsylvania.
The self-paced learning curriculum is framed to be completed in fifteen hours.
You can register for the course and log in at any time to start the program.
There are no prerequisites for the course.
The program instructor for the course is Daniel Lee who is a professor of Electrical and systems engineering.